There are approximately 3.7 million Americans with visual impairment, most of whom have central vision loss and this number is expected to rise as our population ages. Broadcast television, movies and the internet are major sources of information, independence and entertainment, but these media are difficult to use for people with central vision loss. There are few effective assistive devices for using these dynamic media and this is partly because we know relatively little about the perception of natural images viewed with non-foveal vision. This application examines how the visibility of information in natural images depends on contrast and on the presence of nearby features. We introduce new computational techniques that measure and manipulate the visibility of areas within real movies. Next, we use computational and behavioral techniques to segment image locations that are important for perception from areas that are unimportant. These approaches are brought together in a novel, low cost image enhancement system that will operate on standard computers. This system will be evaluated by a group of people with central vision loss and compared side-by- side with alternative methods.

Public Health Relevance

Television, movies and the internet are a major source of information, independence and entertainment, but these media are difficult to use by people with central vision loss and there are few effective assistive devices available. This project contributes directly to public health by developing a low cost image enhancement system for use by this growing population of visually impaired people.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY019281-04
Application #
8320302
Study Section
Special Emphasis Panel (ZRG1-ETTN-R (92))
Program Officer
Wiggs, Cheri
Project Start
2009-09-01
Project End
2013-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$460,944
Indirect Cost
$223,344
Name
Schepens Eye Research Institute
Department
Type
DUNS #
073826000
City
Boston
State
MA
Country
United States
Zip Code
02114
Wiecek, Emily; Lashkari, Kameran; Dakin, Steven C et al. (2015) Metamorphopsia and interocular suppression in monocular and binocular maculopathy. Acta Ophthalmol 93:e318-20
Wallis, Thomas S A; Dorr, Michael; Bex, Peter J (2015) Sensitivity to gaze-contingent contrast increments in naturalistic movies: An exploratory report and model comparison. J Vis 15:3
Wiecek, Emily; Lashkari, Kameran; Dakin, Steven C et al. (2015) Novel quantitative assessment of metamorphopsia in maculopathy. Invest Ophthalmol Vis Sci 56:494-504
Wiecek, Emily; Lashkari, Kameran; Dakin, Steven C et al. (2015) A statistical analysis of metamorphopsia in 7106 amsler grids. Ophthalmology 122:431-3
Harrison, William J; Bex, Peter J (2014) Integrating retinotopic features in spatiotopic coordinates. J Neurosci 34:7351-60
Wiecek, Emily; Dakin, Steven C; Bex, Peter (2014) Metamorphopsia and letter recognition. J Vis 14:1
Kalia, Amy; Lesmes, Luis Andres; Dorr, Michael et al. (2014) Development of pattern vision following early and extended blindness. Proc Natl Acad Sci U S A 111:2035-9
Maiello, Guido; Chessa, Manuela; Solari, Fabio et al. (2014) Simulated disparity and peripheral blur interact during binocular fusion. J Vis 14:13
Wallis, Thomas S A; Taylor, Christopher Patrick; Wallis, Jennifer et al. (2014) Characterization of field loss based on microperimetry is predictive of face recognition difficulties. Invest Ophthalmol Vis Sci 55:142-53
Pelli, Denis G; Bex, Peter (2013) Measuring contrast sensitivity. Vision Res 90:10-4

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